Learn Python programming skills to help you discover, create, and publish data-driven investigations efficiently and effectively in a new online course from the Knight Center for Journalism in the Americas.
“First Python Notebook: Data Analysis on Deadline” runs from May 27 to June 23, 2024. Registration is open now for this paid course, with limited space available. For a fee of $95, register today to secure your spot. This course will be led by Ben Welsh, Reuters News Applications editor, and is designed for journalists who are eager to enhance their storytelling abilities through data analysis. Whether you’re a seasoned journalist looking to expand your skill set or a newcomer eager to dive into the world of data journalism, this course is for you.
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“Data is the foundation for much of the most impactful, most ambitious and most popular journalism,” Welsh said. “To compete in today’s marketplace, journalists need to identify, develop and interview data sources the same way they do human sources.”
In this course, you’ll master Python, a versatile programming language, and Jupyter Notebook, a browser-based interface where you can write, run, remix, and republish code. You’ll also refine your data manipulation skills with pandas, a powerful Python library for handling structured data. Project Jupyter will empower you to document and disseminate your work, fostering transparency.
Course participants will tackle hands-on tasks weekly with real datasets, such as from the Los Angeles Times, learning to navigate, clean, and analyze data, uncovering fascinating narratives along the way.
“Data analysis skills will help you do better stories faster. But, like interviewing, writing, and any other skill, they take practice to master,” Welsh said.
This new paid course is different from the basic free ones the Knight Center has offered in the past, as it goes beyond the fundamentals of the topic and is open to only a limited number of participants. With fewer participants, it offers a more in-depth look at the subject and more personal attention from the instructor, providing a richer learning experience.
Throughout the course, Welsh will host live office hours that will be recorded to ensure that participants who are unable to attend the sessions can access them at a later date.
This course costs $95 and includes full access to course materials and a certificate of completion for those who meet the course requirements.
As an asynchronous course, it gives participants the freedom to learn at their own pace, while still having recommended weekly deadlines. Dive into the modules and activities when it’s most convenient for you; engage in discussions, complete quizzes, and gain practical experience without being tied to rigid schedules.
The course is organized into four weekly modules as well as one introductory module that is available immediately after registration. Each module will cover a different topic through videos lectures and guest interviews, presentations, readings, optional live office hours and discussion forums.
- Module 1 will guide you through the process of installing Jupyter and teach you the basic skills necessary to create an interactive notebook and begin coding. Additionally, it will provide an introduction to pandas.
- Module 2 will dive into practical tasks with a real-world dataset, teaching you how to read, explore, and clean data using pandas.
- Module 3 will show you how to use pandas to examine, interview and improve data sources. It will cover the techniques you need to ask and answer questions with code.
- Lastly, Module 4 will show how to prepare a rigorous finding that’s ready to report.
“I’ve taught similar classes in the past and many graduates have gone on to develop their own stories. I hope the same will be true for many students of this new, expanded edition,” Welsh said.
Don’t miss this opportunity to enhance your data analysis skills and take your journalistic capabilities to a new level.
Register today and join Ben Welsh on a journey that will transform the way you approach data and storytelling.
